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[SPARK-34809][CORE] Enable spark.hadoopRDD.ignoreEmptySplits by default #31909

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[SPARK-34809][CORE] Enable spark.hadoopRDD.ignoreEmptySplits by default #31909

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2 changes: 1 addition & 1 deletion core/src/main/scala/org/apache/spark/internal/config/package.scala
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Expand Up @@ -1037,7 +1037,7 @@ package object config {
.doc("When true, HadoopRDD/NewHadoopRDD will not create partitions for empty input splits.")
.version("2.3.0")
.booleanConf
.createWithDefault(false)
.createWithDefault(true)

private[spark] val SECRET_REDACTION_PATTERN =
ConfigBuilder("spark.redaction.regex")
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2 changes: 2 additions & 0 deletions docs/core-migration-guide.md
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Expand Up @@ -24,6 +24,8 @@ license: |

## Upgrading from Core 3.1 to 3.2

- Since Spark 3.2, `spark.hadoopRDD.ignoreEmptySplits` is set to `true` by default which means Spark will not create empty partitions for empty input splits. To restore the behavior before Spark 3.2, you can set `spark.hadoopRDD.ignoreEmptySplits` to `false`.

- Since Spark 3.2, `spark.eventLog.compression.codec` is set to `zstd` by default which means Spark will not fallback to use `spark.io.compression.codec` anymore.

- Since Spark 3.2, `spark.storage.replication.proactive` is enabled by default which means Spark tries to replenish in case of the loss of cached RDD block replicas due to executor failures. To restore the behavior before Spark 3.2, you can set `spark.storage.replication.proactive` to `false`.
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